Simulating the interactions between physical objects has been and continues to be important to the military and scientific communities. In the military context, the first computers were used to solve differential equations relating to physical motion in order to calculate missile and artillery trajectories. Similarly, the scientific community has sought to model all manner of force interactions from protein molecule interactions to the aerodynamics of flight. However, such approaches have typically used large mainframes and supercomputers and have generally remained out of the hands of the public. Certainly, the idea of using such models for entertainment purposes was not considered.
Presently, computer and console gaming continue to gain in popularity as major sources of entertainment. As video games and related applications gain in popularity, it is not surprising that new technologies have arisen to provide added realism. In particular, the ability to model gameplay dynamics using relationships based upon Newtonian mechanics is now possible.
Currently, many of these physics modeling approaches are processor-intensive and prone to produce defective simulations and object collisions. This places additional demands on software developers' limited time and resources. In turn, this raises costs to the public and lowers the level of realism in many applications. A need therefore exists for techniques that enable the efficient use of processor time while improving the overall level of realism within a given simulated environment.